FootSense: An AI-Augmented Foot-Tactile System for Emotion and Social Regulation in Pervasive Health Contexts
DOI:
https://doi.org/10.4108/eetpht.11.11061Keywords:
foot-tactile interaction, AI-augmented ambient intelligence, emotional regulation, social approach behavior, multi-mechanism model, wearable haptic system, digital health interventionAbstract
INTRODUCTION: FootSense proposes a novel approach to emotional and social regulation through foot-tactile feedback in public spaces. Unlike conventional upper-body haptic systems, it utilizes the feet as a discreet, low-interference interface. By integrating rhythmic, directional, and social-cue tactile stimulation, FootSense modulates emotional states and enhances social interactions in dynamic environments.
OBJECTIVES: This study aims to develop and validate a multi-mechanism foot-tactile model that facilitates emotional relief and social approach in real-world public settings.
METHODS: We developed FootSense, an AI-augmented ambient intelligence system combining behavioral sensing, contextual inference, and adaptive tactile feedback. A two-week field experiment (N=200, five groups) was conducted across four public environments—mall, campus, hospital, and transit hub—to compare rhythmic, directional, and fusion tactile modes. Data were analyzed via ANOVA, mixed-effects modeling, and correlation analysis.
RESULTS: Rhythmic feedback reduced state anxiety (ΔSAI = –7.5, p<.01), directional feedback increased social approach (+83% vs. control, p<.01), and fusion mode showed the strongest overall effects (ΔSAI = –9.3, p<.001; +121% approach frequency). Tactile activation frequency correlated with improvements (r=.46–.51, p<.05). Environmental factors (noise, crowd density) moderated outcomes, with greater benefits in high-stress settings.
CONCLUSION: Embodied, AI-driven foot-tactile feedback offers an effective low-intrusion intervention for emotion regulation and social engagement across diverse public contexts. This work provides a theoretical and practical foundation for integrating AI-augmented haptics into pervasive health and human-centered urban design.
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Copyright (c) 2026 Zhulin Shi, Hao Zhou, Liuqing Chen, Yao Chen, Guanghui Huang, Weiqiang Ying
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